Re: [Help-gsl] constrained fdf multimin

[Tim Fenn]

Sorry to be a continuous bother, but I've made an attempt to
compensate for any changes due to the callback in the stepping
algorithm during the minimization.  Quite simply, it adds a vector
that acts as a multiplier on the step_size, which is scaled according
to the difference between the deltas before and after the callback.
So, for example, if a parameter is initially 0.0, and the delta
according to the gradient is 1.0 but is constrained in the callback to
a limit of 0.5, then the step for that particular parameter is scaled
by 0.5 in any further steps taken for the given gradient.  Once the
gradient is updated, the steps are reset to 1.0.  Therefore, this is
only useful if the minimizer gets caught up in an iteration - which
seems reasonable, but could be adjusted otherwise.

Again, I've attached the patch, which works the same as the previous
implementation.  All my tests have been using fdf minimizers - the
modifications haven't been made to the nelder mead algorithm, but
certainly could be.

Regards,
Tim

-- 
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        Tim Fenn
        address@hidden
        Stanford University, School of Medicine
        James H. Clark Center
        318 Campus Drive, Room E300
        Stanford, CA  94305-5432
        Phone:  (650) 736-1714
        FAX:  (650) 736-1961

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multimin_bound.patch.gz
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